title: Finding optimal control policy in probabilistic Boolean Networks with hard constraints by using integer programming and dynamic programming.
abstract: Boolean Networks (BNs) and Probabilistic Boolean Networks (PBNs) are studied in this paper from the viewpoint of control problems. For BN CONTROL, by applying external control, we propose to derive the network to the desired state within a few time steps. For PBN CONTROL, we propose to find a control sequence such that the network will terminate in the desired state with a maximum probability. Also, we propose to minimise the maximum cost of the terminal state to which the network will enter. We also present a hardness result suggesting that PBN CONTROL is harder than BN CONTROL.
authors.affiliation: Advanced Modelling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong. dlkcissy@hku.hk
authors.forename: Xi
authors.initials: X
authors.lastname: Chen
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Akutsu
authors.forename: Takeyuki
authors.initials: T
authors.lastname: Tamura
authors.forename: Wai-Ki
authors.initials: WK
authors.lastname: Ching
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D008957:Models, Genetic; D015233:Models, Statistical